Dendro-somatic coupling in L5 ACC pyramidal neurons

This code allows reproduction of simulation results from [Mengual2020].

Running the code

To run, make sure all requirements are installed on your machine. Notably, this code uses [BluePyOpt](https://bluepyopt.readthedocs.io/en/latest/) [VanGeit2016] and [NEAT](https://neatdend.readthedocs.io/en/latest/) [Wybo2020].

Clone this repository and compile the ion channels by running from its source directory:

compilechannels channels/

Usage

The optimize the parameters of the ion channels, run the optimizer.optimizeModel() function from a python console.

Optimization results can be plotted with functions in plot_optimization_results.py. The h-current analysis can be ran and plotted with plot_h_analysis.py.

Check out examples.py for specific usage examples of the various optimization or plot functions.

Requirements

• python >= 3.7.6
• neat >= 0.9.0
• neuron >= 7.7.2
• bluepyopt >= 1.9.3
• numpy >= 1.19.2
• matplotlib >= 3.3.2

References

[Mengual2020]

Ulisses Mengual, Willem Wybo, Lotte Spierenburg, Mirko Santello, Walter Senn, and Thomas Nevian (2020) Efficient low-pass dendro-somatic coupling in the apical dendrite of layer 5 pyramidal neurons in the anterior cingulate cortex, In Press.

[VanGeit2016]

Werner Van Geit, Michael Gevaert, Giuseppe Chindemi, Christian Rössert, Jean-Denis Courcol, Eilif Muller, Felix Schürmann, Idan Segev, and Henry Markram (2016) BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience, Front. Neuroinf.

[Wybo2020]

Willem Wybo, Jakob Jordan, Benjamin Ellenberger, Ulisses Mengual, Thomas Nevian, and Walter Senn (2020) Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses, bioRxiv preprint